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Vantor

AI-powered multi-source geospatial intelligence platform

Data Scientist

Data AnalysisUpdated on Nov 11
Full-timeReston, VA, USAIn-person

About the Job

Requirements

  • Must have an active TS/SCI security clearance with CI Polygraph.
  • Must have a bachelor's degree in data science, computer science, engineering, statistics, GIS, or a related discipline; the degree may be substituted with an additional two years of experience.
  • Must have three years of professional experience in data analytics or data engineering roles.
  • Must be proficient in Python and SQL.
  • Must have experience with data-wrangling libraries such as pandas or PySpark and working with APIs or batch-processing tools.
  • Must have experience working with SQL and relational databases.
  • Must understand data modeling, metadata management, and data-governance principles.
  • Must be proficient with Tableau or similar dashboard tools.
  • Must have exposure to cloud platforms such as AWS, Azure, or GCP, especially in data-related services.
  • Must demonstrate attention to detail and documentation practices.
  • Must be able to translate stakeholder questions into clear analytical requirements, metrics, reports, and visualizations.
  • Must be able to communicate findings through written products, dashboards, briefings, and data visualizations.

Responsibilities

  • Prepare, clean, and process structured and unstructured datasets for analysis in collaboration with senior data scientists.
  • Communicate analytical findings, assumptions, limitations, and recommendations to technical and nontechnical audiences.
  • Use Python, SQL, and scripting tools to automate routine data-preparation, data-quality, and reporting tasks.
  • Query, integrate, and analyze data from relational databases, approved APIs, flat files, and enterprise data platforms.
  • Support data-pipeline requirements by documenting source-data issues, business rules, transformations, and validation needs for data engineering teams.
  • Identify data-quality issues, inconsistencies, and gaps, and coordinate with appropriate technical teams to resolve them.
  • Assist in developing and deploying data pipelines in collaboration with data engineering and DevOps teams.
  • Assist with data tagging, metadata capture, and dataset curation for knowledge-management and large language model-enabled workflows.
  • Implement basic statistical analyses, visualizations, and reporting to support exploratory data analysis and hypothesis validation.
  • Maintain detailed documentation of data-preparation methods, scripts, and pipeline configurations.
  • Support integration of data into downstream modeling and large language model/natural language processing workflows.
  • Gain exposure to knowledge-management systems supported by large language models and assist in tagging or curating training datasets for large language model systems.
  • Develop recurring reports, ad hoc analyses, and data visualizations that support operational and leadership decision-making.

Desired Qualifications

  • A master's degree in a technical field such as data science, computer science, or engineering.
  • Experience working with MASINT and TECHINT data.
  • Experience using Clairvoyant or similar orchestration platforms to manage and monitor data pipelines.
  • Familiarity with container-orchestration tools such as Docker, Rancher, or Kubernetes.
  • Basic knowledge of large language model and natural language processing concepts, including using pre-trained models for tasks such as summarization or keyword extraction.
  • Basic familiarity with GIS tools and data.
  • Experience with graph data-science algorithms and graph analytics.
  • Knowledge of enterprise architecture, metadata standards, or master data management.
  • Experience working in agile teams or cross-functional technical environments.
  • Understanding of responsible AI practices and basic data ethics.

About the Company

Vantor

AI-powered multi-source geospatial intelligence platform

Vantor provides an AI-powered spatial intelligence platform that creates a real-time, unified picture from space, air, and ground sensors. Its Tensorglobe data engine fuses satellite imagery, drone feeds, and ground sensors to build a living 3D digital Earth and automates the entire intelligence cycle from tasking to analysis. Key products include WorldView for high-resolution imagery tasking, Raptor for GPS-denied navigation, and Sentry for automated site monitoring. Unlike competitors that mainly sell raw imagery, Vantor offers an integrated, subscription-based geospatial workflow and digital twin as a service, helping defense, intelligence, and commercial customers make faster, more informed decisions through a shared AI-ready view of the world.

Company size
1,001-5,000
Company stage
IPO
Headquarters
San Juan, Puerto Rico
Founded
1957

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